Wading Into Data

On the first day of the Building a Digital Portfolio institute, I told the group that my biggest anxiety about using digital art history methods to investigate my dissertation topic had to do with limited access to digitized data. I went on to complain in my first blog post that it is presently impossible to carry out a visualization project on fifteenth-century Naples because no structured data set exists for the topic. In the course of this past week, I have already begun to build my own data set to remedy this problem. This new project is one that I have contemplated for over a year now, and I have failed to get started because it seemed too large a project for me to undertake alone at this stage in my dissertation research. The idea of building a data set also made me uncomfortable because so many aspects of my dissertation topic lack firm documentary evidence—a point that was made even more clear to me by the word cloud of my dissertation I created using Voyant Tools, which includes the high-frequency words ‘probably’ and ‘likely.’

Voyant word cloud of my dissertation, with the words ‘probably’ and ‘likely’ included.

Although there is much about my dissertation that I can’t responsibly confine to a single cell in a spreadsheet, I think there is a great deal that I can learn about fifteenth-century Neapolitan art, and the patronage of King Ferrante in particular, by trying to visualize the limited documentary evidence that does exist. Fortunately for the Neapolitanists of the world, Gaetano Filangieri compiled six volumes of primary source material on art of the Kingdoms of Naples and Sicily, (Documenti per la storia, le arti e le industrie delle provincie napoletane)published 1883-1891. These volumes (now available via Hathi Trust) are invaluable, since many of the sources Filangieri compiled were destroyed in the bombing of the Neapolitan archives in 1943.

Rather than continuing to bemoan the lack of digital source material in my field, I’ve decided to focus my efforts on building a structured data set from this one critical source that is available. My project will focus specifically on Filangieri’s volumes 5 & 6, which provide chronological lists of archival material (often including the artist’s birthplace, trade, date and description of the commission, patron’s name, and the amount an artist was paid). Within those volumes, I’m focusing on records from the dates of King Ferrante’s reign, 1458-1494.

So, what do I hope to accomplish with this data?

I’m interested in visualizing, for example, the most active patrons and artists in the kingdom, and the networks among them. I want to examine the geographic origins of artists working in the Kingdom of Naples and to consider different patrons’ preferences for hiring artists from particular regions. There are many other questions relative to artists’ origins, trades, and earnings that I could study through this data set, too. These are quite elementary art historical questions, but because scholarship on Neapolitan art of the early modern period lags behind that of other Italian cities, these basic questions still require attention, and I think data visualization could be a useful way to address them.

I have only worked through the letters A, B, and part of the C surnames in Filangieri’s publication, and I have already made some interesting realizations. This morning I uploaded a PDF version of my data set to Voyant to examine the geographic origins of the artists working in the Kingdom. I was surprised to find that Cava dei Tirreni appears to have been a major producer of artists in this period.

Voyant Word Cloud of the origins of artists working in the Kingdom of Naples between 1458-1494.

I then drilled down a bit further in my data, this time using Tableau, to see how the different trades of artists coming out of Cava dei Tirreni compared to those from Naples. I found that Naples produced many painters, silversmiths, goldsmiths, glassmakers, tailors, and sculptors, while Cava dei Tirreni specialized in stonemasons, architects, and builders.

Tableau Bubble Plot of common trades in Naples and Cava dei Tirreni.

Of course, this data set is skewed because a couple of large families of builders from Cava dei Tirreni have surnames in the early part of the alphabet. Although I can’t make any conclusions until I have visualized the entire data set, I’m already getting excited about the power of tools like Tableau and Palladio to macroscopically examine characteristics of fifteenth-century Neapolitan art. The challenge for me at this early stage (in addition to building a tidy, error-free data set), is deciding which tools and types of visualizations are best suited to the questions I’m asking.